1. Field of the Invention
The present invention relates, in general, to machine processing of text and language, and, more particularly, to a method and apparatus including a software implementation for machine assisted translation.
2. Statement of the Problem
Translation of text from one language to another is often a tedious task requiring the efforts of a skilled translator. Soon after the advent of computers, researchers began to use computers as an aid for natural language translation. The earliest machine translation (MT) systems relied on large bilingual dictionaries where entries for words of the source language (SL) gave one or more equivalents in the target language (TL). It quickly became apparent that dictionary rules for syntax and grammar were so complex that experts could not develop a comprehensive set of rules to describe the language. These problems have proven so intractable that most efforts at machine translation have been abandoned.
Throughout the world, multilingual cultures and multinational trade create an increasing demand for translation services. The demand for translation of commercial and technical document translation represents a large and growing segment of the translation market. Examples of such documents are contracts, instruction manuals, forms, and computer software. Often when a product or service is "localized" to a new foreign market, a great deal of documentation must be translated, creating a need for cost-effective translation. Because commercial and technical information is often detailed and precise, accurate translations continue to be demanded.
Machine translation (MT) systems are usually classified as either direct, transfer-based, or interlingua-based. In the direct approach, there are no intermediate representations between the source language and the target language. The source language text is processed "directly" in order to transform it into the target text, essentially a word-to-word translation with some adjustments. This approach is not followed by any MT system at present on account of a perceived weakness attributable to ignoring all aspects of the internal structure of sentences.
In the transfer-based approach, information from the various stages of analysis from the source text is transferred to the corresponding stages of the generation of the target text, for example, transfer is achieved by setting up correspondences at the lexical level, at the grammar level, or at the level of the structure built by the grammar, and so forth. The transfer method operates only on a particular pair of languages, and so must be specifically and painstakingly created for each pair of languages.
The interlingua-based approach depends on an assumption that a suitable intermediate representation can be defined such that the source text can be mapped into the intermediate representation that can then be mapped into the target text. In principle, this approach is clearly attractive because, unlike the transfer-based approach, it is not necessary to build a separate transfer program for each pair of languages. However, it is not clear whether a truly language-independent intermediate representation can be devised. Current interlingua-based systems are much less ambitious about their claims to the universality of the intermediate representation. For a high-quality translation, it is often necessary to have access to some particular aspects of the source and target languages.
In the transfer-based approach, there have been some recent advances. In the development of mathematical and computational models of grammars there is increasing emphasis on locating syntactic as well as semantic information directly with the lexical items by associating structures with the lexical items and defining operations for composing these objects. From this perspective, all the information particular to a language is encapsulated in the lexical items and the structures associated with them. Different languages will be distinguished at this level, but not with respect to the operations for composing these structures, which are the same for all languages, on this approach. The idea then, is to define all bilingual correspondences at this level. It remains to be seen if this approach can be carried out across a variety of languages.
Some existing MT systems require documents to be written in highly constrained texts. Such a system is useful for preparing manuals in different languages. Here the system is really not translating a manual written in one natural language into a set of other natural languages, but rather is generating multilingual texts from a highly constrained text, thus avoiding many problems in conventional MT.
Recently, research has focused on ways of using machines to assist human translators rather than to autonomously perform translations. This approach is referred to as machine assisted translation or interactive translation. Systems are available that produce high-quality translations of business correspondence using pre-translated fragments with some translations filled in by human translators. An example of a machine assisted translation tool is a translation memory (TM). A translation memory is a database that collects translations as they are performed along with the source language equivalents. After a number of translations have been performed and stored in the translation memory, it can be accessed to assist new translations where the new translation includes identical or similar source language text as has been included in the translation memory.
The advantage of such a system is that it can in theory leverage existing MT technology to make the translator more efficient, without sacrificing the traditional accuracy provided by a human translator. It makes translations more efficient by ensuring that the translator never has to translate the same source text twice. However, because translation memories require large data files that must be searched to retrieve matching text, they have been slow. Often a skilled human translator can perform the translation more quickly than the machine can locate the pre-translated material. A continuing need exists for translation memory tools with rapid search and retrieval capability.
Translation memories are most useful when they are able to locate not only identical matches, but also approximate or "fuzzy matches." Fuzzy matching facilitates retrieval of text that differs slightly in word order, morphology, case, or spelling. The approximate matching is necessary because of the large variety possible in natural language texts. Examples of systems using fuzzy matching include Translator's Workbench for Windows by Trados and Deja Vu, published by Atril. The particular implementation of a fuzzy matching system is critical to performance, however.
Because TMs do not analyze syntax or grammar they are more language independent than other translation techniques. In practice, however, it has been difficult to implement search software that is truly language independent. In particular, existing search engines are word based, which is to say that they rely on the word as a basic element in accomplishing the search. This is particularly true of fuzzy search methods. In each language, words change in unique ways to account for changes in gender, plurality, tense, and the like. Hence, word-based systems cannot be truly language independent because the words themselves are inherently language oriented. It has been a continuing difficulty to develop fast, accurate fuzzy text search methods.
Concordances are another tool commonly used by translators. Electronic concordances are files having text strings (i.e., words, phrases or sentences) matched with the context in which the word appeared in a document. When a translator is unsure of the meaning to be given a particular word, the concordance can demonstrate how the word is used in several different contexts. This information allows more accurate selection of translations to accurately reflect the meaning of a source language document. Electronic concordances include text searching software that allows the translator to extract all text strings in a library that include a desired word or phrase. The extracted text strings can be examined quickly to gain a greater understanding of how a particular word or phase is used in context.
Multilingual natural language processing represents a growing need and opportunity in the field of international commerce and communication. Machine assisted translation tools are needed to make document translation more efficient and less costly. Further, machine assisted translation tools are needed that efficiently leverage the large amount of stored knowledge available as pre-translated commercial and technical documents. Specifically, a need exists for a translation memory tool that is language independent and provides accurate, rapid fuzzy retrieval of pre-translated material.
3. Solution to the Problem
The above problems are solved by the present invention by translation tools that are inherently language independent. Differential weighting of novel text segments provides an ability to fuzzy match words, phrases, as well as full sentences and multiple sentence documents. Fuzzy matching permits effective fuzzy concordance searching on sub-strings within sentences.